Can artificial intelligence rescue America’s fiscal future?

Can Artificial Intelligence Rescue America’s Fiscal Future?

The national debt is on a concerning trajectory. The Congressional Budget Office (CBO) projected the debt climbing to 118 percent of GDP by 2035 from 100 percent this year. Recent legislative action has added another 10 percentage points or so, resulting in a sub-optimal fiscal outlook.

Amidst this worsening situation, a compelling theory has emerged: perhaps artificial intelligence could generate enough economic growth to stabilize or even reverse America’s dangerous debt path. The idea is tempting for policymakers: if AI truly acts as a transformative, general-purpose technology akin to electricity or the internet, then accelerated productivity growth could lead to a significant revenue windfall. This influx of funds might offset deficits and debt, potentially reducing the need for politically challenging spending cuts or tax increases.

There's historical basis for such optimism. CBO data shows that total factor productivity (TFP) growth, a key measure of economic efficiency often boosted by technology, averaged 1.6 percent to 1.8 percent annually for over a century, driven by prior waves of innovation.

However, recent research highlights the limitations of conventional policy in achieving this kind of growth. A paper by Douglas Elmendorf, Glenn Hubbard, and Zachary Liscow (EHL) used CBO scenarios to model the impact of sustained TFP growth. They found that a hypothetical 0.5 percentage point annual increase in TFP growth could reduce debt held by the public by 12 percentage points of GDP over the next decade and a substantial 42 percentage points over 30 years. This level of acceleration would put the US economy back on its historical productivity trend.

Crucially, the EHL paper examined various plausible policy reforms – covering areas like immigration, housing, permitting, R&D, and business taxes. Their stark conclusion was that none of these policy changes, individually or combined, came close to generating the sustained 0.5 percentage point TFP growth surge needed to achieve significant debt reduction through growth alone. They emphasized that while growth-enhancing reforms are beneficial, they cannot, by themselves, stabilize the national debt.

This is where the AI optimism enters the broader debate. While the EHL paper did not explicitly include AI in its policy analysis, the core question becomes: could AI be the disruptive force that delivers the unprecedented TFP acceleration required?

If AI technologies indeed spark a historic step-change in productivity, similar to past general-purpose technologies, the fiscal benefits could theoretically be immense. Joe Davis, Vanguard’s global chief economist, assigns a 45–55 percent probability to a “productivity surge” scenario driven by AI becoming economically transformative by the 2030s. Under this optimistic outcome, AI could help control inflation while higher tax revenues from a faster-growing economy stabilize the accumulating debt – potentially mirroring the favorable fiscal conditions of the 1990s.

Yet, prudent fiscal policymaking demands caution. Davis himself acknowledges a significant 30–40 percent chance that AI might disappoint, failing to deliver the hoped-for productivity gains. In this scenario, productivity would remain sluggish, and the deficits would continue their upward climb, unimpeded by a tech-fueled revenue boost.

The case for AI-driven economic optimism is reasonable, given the technology's potential. However, the future impact of AI on productivity is far from certain. Basing America’s fiscal future solely on the hope that AI will generate sufficient growth to solve the debt problem would be a massive and irresponsible gamble. Policymakers should not bank on technological salvation to avoid difficult fiscal choices.

A more responsible approach involves a dual strategy. First, actively pursue policies that are genuinely growth-friendly and supportive of innovation, including AI development and adoption. This involves streamlining regulations (like permitting reform), increasing investment in science and R&D, encouraging business investment, and implementing high-skilled immigration policies. Second, and critically, policymakers must simultaneously address the underlying drivers of the debt trajectory through direct fiscal measures. This means tackling entitlement spending reforms sooner rather than later.

While we can hope that the AI productivity boom materializes and provides some fiscal relief, it is essential to budget based on a more realistic, linear assessment of growth rather than betting on an exponential technological leap. The future is uncertain, and relying on AI alone to rescue the nation's finances is a risk America cannot afford to take.

Hope for exponential growth, but budget for linear reality.